In Figure REF , we show editing performed on real images mapped into novel domains, using several off-the-shelf methods. In particular, we use StyleCLIP [1]} to edit expression and hairstyle, StyleFlow [2]} to edit pose, and InterfaceGAN [3]} to edit age. In all cases we use the original implementations and pre-trained models where such are available. As can be seen, the adapted generator maintains a similar capacity for semantic, latent-based editing. Notably, the directions that control semantic attributes in the new generator are aligned with those of the source, enabling the use of a host of existing editing methods and pre-trained models, and ensuring that we do not need to re-train or re-discover such directions for each new domain.
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